UK_L20 Model

#

# UKL20 Model

#

require(dse)

require(matlab)

# Measurement Matrix # Overall-(CO2+LU),(EF+CO2+EG- L),(LU+L+N+EF - KOF)

# 

#      EN.ATM.CO2E.KT EG.USE.COMM.KT.OE NY.GDP.MKTP.KD SL.TLF.TOTL.IN SP.POP.TOTL

#[1,]        -0.3191            0.2111        0.41693         0.3147     0.40422

#[2,]         0.3919            0.5579        0.02489        -0.3210    -0.02218

#[3,]        -0.1267            0.2253        0.04727         0.4173     0.31838

#     SL.UEM.TOTL.ZS      KOF      EF      HDI

#[1,]        -0.3243  0.38640 0.01132  0.40349

#[2,]        -0.1260  0.06557 0.63561  0.08302

#[3,]         0.7125 -0.22818 0.28185 -0.12800

# Fraction of Variance 

#[1] 0.6343 0.8797 0.9344 0.9766 0.9890 0.9969 0.9990 0.9998 1.0000

#

AIC <- function(model) {informationTestsCalculations(model)[3]}

f <- matrix( c(1.00000000,  0.000000000,  0.0000000000,  0.000000000,

                     0.15156250,  1.018572111,  0.0002269249,  0.005172694,

                    -0.06983131, -0.126397980,  1.0576660915, -0.275455949,

                     0.04382693, -0.001373313, -0.0298119308 , 0.926069637

),byrow=TRUE,nrow=4,ncol=4)

#

# To Stabilize System, uncomment next line

# f[2,2] <- f[3,3] <- f[4,4]

h <- matrix(c(0,    1,    0 ,   0,

                     0,    0,    1,    0,

                     0,    0,    0 ,   1

),byrow=TRUE,nrow=3,ncol=4)

k <- f[1:4,2:4,drop=FALSE]

UK <- SS(F=f,H=h,K=k,z0=c( 1.000000, -3.185388, -2.514388, -1.465725),

              output.names=c("UK1","UK2","UK3"))

UK;

stability(SS(F=f[2:4,2:4],H=eye(3), R=eye(3),Q=eye(3)))

shockDecomposition(toSSChol(UK))

#tfplot(simulate(UK,sampleT=50,start=1))

UK.data <- simulate(UK,sampleT=50,noise=matrix(0,50,2),start=1)

m <- l(UK,UK.data)

#tfplot(m)

UK.f <- forecast(m,horizon=50)

tfplot(UK.f)

AIC(m)